At least, that’s what preliminary data from the International Energy Agency say. It seems the big difference is China. The Chinese made more electricity from renewable sources, such as hydropower, solar and wind, and burned less coal.

In fact, a report by Greenpeace says that from April 2014 to April 2015, China’s carbon emissions dropped by an amount equal to the entire carbon emissions of the United Kingdom!

I want to check this, because it would be wonderful if true: a 5% drop. They say that if this trend continues, China will close out 2015 with the biggest reduction in CO2 emissions every recorded by a single country.

The International Energy Agency also credits Europe’s improved attempts to cut carbon emissions for the turnaround. In the US, carbon emissions has basically been dropping since 2006—with a big drop in 2009 due to the economic collapse, a partial bounce-back in 2010, but a general downward trend.

In the last 40 years, there have only been 3 times in which emissions stood still or fell compared to the previous year, all during global economic crises: the early 1980’s, 1992, and 2009. In 2014, however, the global economy expanded by 3%.

CO2 concentrations haven’t been this high in millions of years. Even more alarming is the rate of increase in the last five decades and the fact that CO2 stays in the atmosphere for hundreds or thousands of years. This milestone is a wake up call that our actions in response to climate change need to match the persistent rise in CO2. Climate change is a threat to life on Earth and we can no longer afford to be spectators.

Russian scientists have recently found more new craters in Siberia, apparently formed by explosions of methane. Three were found last summer. They looked for more using satellite photos… and found more!

“What I think is happening here is, the permafrost has been acting as a cap or seal on the ground, through which gas can’t permeate,” says Paul Overduin, a permafrost expert at the Alfred Wegener Institute in Germany. “And it reaches a particular temperature where there’s not enough ice in it to act that way anymore. And then gas can rush out.”

It’s rather dramatic. Some Russian villagers have even claimed to see flashes in the distance when these explosions occur. But how bad is it?

The Siberian Times

An English-language newspaper called The Siberian Times has a good article about these craters, which I’ll quote extensively:

Respected Moscow scientist Professor Vasily Bogoyavlensky has called for ‘urgent’ investigation of the new phenomenon amid safety fears.

Until now, only three large craters were known about in northern Russia with several scientific sources speculating last year that heating from above the surface due to unusually warm climatic conditions, and from below, due to geological fault lines, led to a huge release of gas hydrates, so causing the formation of these craters in Arctic regions.

Two of the newly-discovered large craters—also known as funnels to scientists—have turned into lakes, revealed Professor Bogoyavlensky, deputy director of the Moscow-based Oil and Gas Research Institute, part of the Russian Academy of Sciences.

Examination using satellite images has helped Russian experts understand that the craters are more widespread than was first realised, with one large hole surrounded by as many as 20 mini-craters, The Siberian Times can reveal.

Four Arctic craters: B1 – famous Yamal hole in 30 kilometers from Bovanenkovo, B2 – recently detected crater in 10 kilometers to the south from Bovanenkovo, B3 – crater located in 90 kilometers from Antipayuta village, B4 – crater located near Nosok village, on the north of Krasnoyarsk region, near Taimyr Peninsula. Picture: Vasily Bogoyavlensky.

‘We know now of seven craters in the Arctic area,’ he said. ‘Five are directly on the Yamal peninsula, one in Yamal Autonomous district, and one is on the north of the Krasnoyarsk region, near the Taimyr peninsula.

‘We have exact locations for only four of them. The other three were spotted by reindeer herders. But I am sure that there are more craters on Yamal, we just need to search for them.

‘I would compare this with mushrooms: when you find one mushroom, be sure there are few more around. I suppose there could be 20 to 30 craters more.’

He is anxious to investigate the craters further because of serious concerns for safety in these regions.

The study of satellite images showed that near the famous hole, located in 30 kilometres from Bovanenkovo are two potentially dangerous objects, where the gas emission can occur at any moment.

Satellite image of the site before the forming of the Yamal hole (B1). K1 and the red outline show the hillock (pingo) formed before the gas emission. Yellow outlines show the potentially dangerous objects. Picture: Vasily Bogoyavlensky.

He warned: ‘These objects need to be studied, but it is rather dangerous for the researchers. We know that there can occur a series of gas emissions over an extended period of time, but we do not know exactly when they might happen.

‘For example, you all remember the magnificent shots of the Yamal crater in winter, made during the latest expedition in Novomber 2014. But do you know that Vladimir Pushkarev, director of the Russian Centre of Arctic Exploration, was the first man in the world who went down the crater of gas emission?

‘More than this, it was very risky, because no one could guarantee there would not be new emissions.’

Professor Bogoyavlensky told The Siberian Times: ‘One of the most interesting objects here is the crater that we mark as B2, located 10 kilometres to the south of Bovanenkovo. On the satellite image you can see that it is one big lake surrounded by more than 20 small craters filled with water.

‘Studying the satellite images we found out that initially there were no craters nor a lake. Some craters appeared, then more. Then, I suppose that the craters filled with water and turned to several lakes, then merged into one large lake, 50 by 100 metres in diameter.

‘This big lake is surrounded by the network of more than 20 ‘baby’ craters now filled with water and I suppose that new ones could appear last summer or even now. We now counting them and making a catalogue. Some of them are very small, no more than 2 metres in diameter.’

‘We have not been at the spot yet,’ he said. ‘Probably some local reindeer herders were there, but so far no scientists.’

He explained: ‘After studying this object I am pretty sure that there was a series of gas emissions over an extended period of time. Sadly, we do not know, when exactly these emissions occur, i.e. mostly in summer, or in winter too. We see only the results of this emissions.’

The object B2 is now attracting special attention from the researchers as they seek to understand and explain the phenomenon. This is only 10km from Bovanenkovo, a major gas field, developed by Gazprom, in the Yamalo-Nenets Autonomous Okrug. Yet older satellite images do not show the existence of a lake, nor any craters, in this location.

Not only the new craters constantly forming on Yamal show that the process of gas emission is ongoing actively.

Professor Bogoyavlensky shows the picture of one of the Yamal lakes, taken by him from the helicopter and points on the whitish haze on its surface.

He commented: ‘This haze that you see on the surface shows that gas seeps that go from the bottom of the lake to the surface. We call this process ‘degassing’.

‘We do not know, if there was a crater previously and then turned to lake, or the lake formed during some other process. More important is that the gases from within are actively seeping through this lake.

‘Degassing was revealed on the territory of Yamal Autonomous District about 45 years ago, but now we think that it can give us some clues about the formation of the craters and gas emissions. Anyway, we must research this phenomenon urgently, to prevent possible disasters.’

Professor Bogoyavlensky stressed: ‘For now, we can speak only about the results of our work in the laboratory, using the images from space.

‘No one knows what is happening in these craters at the moment. We plan a new expedition. Also we want to put not less than four seismic stations in Yamal district, so they can fix small earthquakes, that occur when the crater appears.

‘In two cases locals told us that they felt earth tremors. The nearest seismic station was yet too far to register these tremors.

‘I think that at the moment we know enough about the crater B1. There were several expeditions, we took probes and made measurements. I believe that we need to visit the other craters, namely B2, B3 and B4, and then visit the rest three craters, when we will know their exact location. It will give us more information and will bring us closer to understanding the phenomenon.’

He urged: ‘It is important not to scare people, but to understand that it is a very serious problem and we must research this.’

In an article for Drilling and Oil magazine, Professor Bogoyavlensky said the parapet of these craters suggests an underground explosion.

‘The absence of charred rock and traces of significant erosion due to possible water leaks speaks in favour of mighty eruption (pneumatic exhaust) of gas from a shallow underground reservoir, which left no traces on soil which contained a high percentage of ice,’ he wrote.

‘In other words, it was a gas-explosive mechanism that worked there. A concentration of 5-to-16% of methane is explosive. The most explosive concentration is 9.5%.’

Gas probably concentrated underground in a cavity ‘which formed due to the gradual melting of buried ice’. Then ‘gas was replacing ice and water’.

‘Years of experience has shown that gas emissions can cause serious damage to drilling rigs, oil and gas fields and offshore pipelines,’ he said. ‘Yamal craters are inherently similar to pockmarks.

‘We cannot rule out new gas emissions in the Arctic and in some cases they can ignite.’

This was possible in the case of the crater found at Antipayuta, on the Yamal peninsula.

‘The Antipayuta residents told how they saw some flash. Probably the gas ignited when appeared the crater B4, near Taimyr peninsula. This shows us, that such explosion could be rather dangerous and destructive.

‘We need to answer now the basic questions: what areas and under what conditions are the most dangerous? These questions are important for safe operation of the northern cities and infrastructure of oil and gas complexes.’

Crater B4 located near Nosok village, on the north of Krasnoyarsk region, near Taimyr Peninsula. Picture: local residents.

How bad is it?

Since methane is a powerful greenhouse gas, some people are getting nervous. If global warming releases the huge amounts of methane trapped under permafrost, will that create more global warming? Could we be getting into a runaway feedback loop?

The Washington Post has a good article telling us to pay attention, but not panic:

David Archer of the University of Chicago, a famous expert on climate change and the carbon cycle, took a look at thes craters and did some quick calculations. He estimated that “it would take about 20,000,000 such eruptions within a few years to generate the standard Arctic Methane Apocalypse that people have been talking about.”

More importantly, people are measuring the amount of methane in the air. We know how it’s doing. For example, you can make graphs of methane concentration here:

Click on a northern station like Alert, the scary name of a military base and research station in Nunavut—the huge northern province in Canada:

(Alert is on the very top, near Greenland.)

Choose Carbon cycle gases from the menu at right, and click on Time series. You’ll go to another page, and then choose Methane—the default choice is carbon dioxide. Go to the bottom of the page and click Submit and you’ll get a graph like this:

Methane has gone up from about 1750 to 1900 nanomoles per mole from 1985 to 2015. That’s a big increase—but not a sign of incipient disaster.

A larger perspective might help. Apparently from 1750 to 2007 the atmospheric CO2 concentration increased about 40% while the methane concentration has increased about 160%. The amount of additional radiative forcing due to CO2 is about 1.6 watts per square meter, while for methane it’s about 0.5:

So, methane is significant, and increasing fast. So far CO2 is the 800-pound gorilla in the living room. But I’m glad Russian scientists are doing things like this:

The latest expedition to Yamal crater was initiated by the Russian Center of Arctic Exploration in early November 2014. The researchers were first in the world to enter this crater. Pictures: Vladimir Pushkarev/Russian Center of Arctic Exploration

Electric power companies complain about wind power because it’s intermittent: if suddenly the wind stops, they have to bring in other sources of power.

This is no big deal if we only use a little wind. Across the US, wind now supplies 4% of electric power; even in Germany it’s just 8%. The problem starts if we use a lot of wind. If we’re not careful, we’ll need big fossil-fuel-powered electric plants when the wind stops. And these need to be turned on, ready to pick up the slack at a moment’s notice!

So, a few years ago Xcel Energy, which supplies much of Colorado’s power, ran ads opposing a proposal that it use renewable sources for 10% of its power.

But now things have changed. Now Xcel gets about 15% of their power from wind, on average. And sometimes this spikes to much more!

What made the difference?

Every few seconds, hundreds of turbines measure the wind speed. Every 5 minutes, they send this data to high-performance computers 100 miles away at the National Center for Atmospheric Research in Boulder. NCAR crunches these numbers along with data from weather satellites, weather stations, and other wind farms – and creates highly accurate wind power forecasts.

With better prediction, Xcel can do a better job of shutting down idling backup plants on days when they’re not needed. Last year was a breakthrough year – better forecasts saved Xcel nearly as much money as they had in the three previous years combined.

It’s all part of the emerging smart grid—an intelligent network that someday will include appliances and electric cars. With a good smart grid, we could set our washing machine to run when power is cheap. Maybe electric cars could store solar power in the day, use it to power neighborhoods when electricity demand peaks in the evening – then recharge their batteries using wind power in the early morning hours. And so on.

References

I would love if it the Network Theory project could ever grow to the point of helping design the smart grid. So far we are doing much more ‘foundational’ work on control theory, along with a more applied project on predicting El Niños. I’ll talk about both of these soon! But I have big hopes and dreams, so I want to keep learning more about power grids and the like.

The first is fun and easy to read. The second has more technical details. It describes the software used (the picture on top of this article shows a bit of this), and also some of the underlying math and physics. Let me quote a bit:

High-resolution Mesoscale Ensemble Prediction Model (EPM)

It is known that atmospheric processes are chaotic in nature. This implies that even small errors in the model initial conditions combined with the imperfections inherent in the NWP model formulations, such as truncation errors and approximations in model dynamics and physics, can lead to a wind forecast with large errors for certain weather regimes. Thus, probabilistic wind prediction approaches are necessary for guiding wind power applications. Ensemble prediction is at present a practical approach for producing such probabilistic predictions. An innovative mesoscale Ensemble Real-Time Four Dimensional Data Assimilation (E-RTFDDA) and forecasting system that was developed at NCAR was used as the basis for incorporating this ensemble prediction capability into the Xcel forecasting system.

Ensemble prediction means that instead of a single weather forecast, we generate a probability distribution on the set of weather forecasts. The paper has references explaining this in more detail.

We had a nice discussion of wind power and the smart grid over on G+. Among other things, John Despujols mentioned the role of ‘smart inverters’ in enhancing grid stability:

A solar inverter converts the variable direct current output of a photovoltaic solar panel into alternating current usable by the electric grid. There’s a lot of math involved here—click the link for a Wikipedia summary. But solar inverters are getting smarter.

Wild fluctuations

While the solar inverter has long been the essential link between the photovoltaic panel and the electricity distribution network and converting DC to AC, its role is expanding due to the massive growth in solar energy generation. Utility companies and grid operators have become increasingly concerned about managing what can potentially be wildly fluctuating levels of energy produced by the huge (and still growing) number of grid-connected solar systems, whether they are rooftop systems or utility-scale solar farms. Intermittent production due to cloud cover or temporary faults has the potential to destabilize the grid. In addition, grid operators are struggling to plan ahead due to lack of accurate data on production from these systems as well as on true energy consumption.

In large-scale facilities, virtually all output is fed to the national grid or micro-grid, and is typically well monitored. At the rooftop level, although individually small, collectively the amount of energy produced has a significant potential. California estimated it has more than 150,000 residential rooftop grid-connected solar systems with a potential to generate 2.7 MW.

However, while in some systems all the solar energy generated is fed to the grid and not accessible to the producer, others allow energy generated to be used immediately by the producer, with only the excess fed to the grid. In the latter case, smart meters may only measure the net output for billing purposes. In many cases, information on production and consumption, supplied by smart meters to utility companies, may not be available to the grid operators.

Getting smarter

The solution according to industry experts is the smart inverter. Every inverter, whether at panel level or megawatt-scale, has a role to play in grid stability. Traditional inverters have, for safety reasons, become controllable, so that they can be disconnected from the grid at any sign of grid instability. It has been reported that sudden, widespread disconnects can exacerbate grid instability rather than help settle it.

Smart inverters, however, provide a greater degree of control and have been designed to help maintain grid stability. One trend in this area is to use synchrophasor measurements to detect and identify a grid instability event, rather than conventional ‘perturb-and-observe’ methods. The aim is to distinguish between a true island condition and a voltage or frequency disturbance which may benefit from additional power generation by the inverter rather than a disconnect.

Smart inverters can change the power factor. They can input or receive reactive power to manage voltage and power fluctuations, driving voltage up or down depending on immediate requirements. Adaptive volts-amps reactive (VAR) compensation techniques could enable ‘self-healing’ on the grid.

Two-way communications between smart inverter and smart grid not only allow fundamental data on production to be transmitted to the grid operator on a timely basis, but upstream data on voltage and current can help the smart inverter adjust its operation to improve power quality, regulate voltage, and improve grid stability without compromising safety. There are considerable challenges still to overcome in terms of agreeing and evolving national and international technical standards, but this topic is not covered here.

The benefits of the smart inverter over traditional devices have been recognized in Germany, Europe’s largest solar energy producer, where an initiative is underway to convert all solar energy producers’ inverters to smart inverters. Although the cost of smart inverters is slightly higher than traditional systems, the advantages gained in grid balancing and accurate data for planning purposes are considered worthwhile. Key features of smart inverters required by German national standards include power ramping and volt/VAR control, which directly influence improved grid stability.

(Figure SPM.10) Global mean surface temperature increase as a function of cumulative total global CO2 emissions from various lines of evidence. Multi-model results from a hierarchy of climate-carbon cycle models for each RCP until 2100 are shown with coloured lines and decadal means (dots). Some decadal means are indicated for clarity (e.g., 2050 indicating the decade 2041−2050). Model results over the historical period (1860–2010) are indicated in black. The coloured plume illustrates the multi-model spread over the four RCP scenarios and fades with the decreasing number of available models in RCP8.5. The multi-model mean and range simulated by CMIP5 models, forced by a CO2 increase of 1% per year (1% per year CO2 simulations), is given by the thin black line and grey area. For a specific amount of cumulative CO2 emissions, the 1% per year CO2 simulations exhibit lower warming than those driven by RCPs, which include additional non-CO2 drivers. All values are given relative to the 1861−1880 base period. Decadal averages are connected by straight lines.

(Click to enlarge.)

The chart is a little hard to follow, but the main idea should be clear: whichever experiment we carry out, the results tend to lie on a straight line on this graph. You do get a slightly different slope in one experiment, the “1% percent CO2 increase per year” experiment, where only CO2 rises, and much more slowly than it has over the last few decades. All the more realistic scenarios lie in the orange band, and all have about the same slope.

This linear relationship is a useful insight, because it means that for any target ceiling for temperature rise (e.g. the UN’s commitment to not allow warming to rise more than 2°C above pre-industrial levels), we can easily determine a cumulative emissions budget that corresponds to that temperature. So that brings us to the most important paragraph in the entire report, which occurs towards the end of the summary for policymakers:

Limiting the warming caused by anthropogenic CO2 emissions alone with a probability of >33%, >50%, and >66% to less than 2°C since the period 1861–1880, will require cumulative CO2 emissions from all anthropogenic sources to stay between 0 and about 1560 GtC, 0 and about 1210 GtC, and 0 and about 1000 GtC since that period respectively. These upper amounts are reduced to about 880 GtC, 840 GtC, and 800 GtC respectively, when accounting for non-CO2 forcings as in RCP2.6. An amount of 531 [446 to 616] GtC, was already emitted by 2011.

Unfortunately, this paragraph is a little hard to follow, perhaps because there was a major battle over the exact wording of it in the final few hours of inter-governmental review of the “Summary for Policymakers”. Several oil states objected to any language that put a fixed limit on our total carbon budget. The compromise was to give several different targets for different levels of risk.

Let’s unpick them. First notice that the targets in the first sentence are based on looking at CO2 emissions alone; the lower targets in the second sentence take into account other greenhouse gases, and other earth systems feedbacks (e.g. release of methane from melting permafrost), and so are much lower. It’s these targets that really matter:

• To give us a one third (33%) chance of staying below 2°C of warming over pre-industrial levels, we cannot ever emit more than 880 gigatonnes of carbon.

• To give us a 50% chance, we cannot ever emit more than 840 gigatonnes of carbon.

• To give us a 66% chance, we cannot ever emit more than 800 gigatonnes of carbon.

Since the beginning of industrialization, we have already emitted a little more than 500 gigatonnes. So our remaining budget is somewhere between 300 and 400 gigatonnes of carbon. Existing known fossil fuel reserves are enough to release at least 1000 gigatonnes. New discoveries and unconventional sources will likely more than double this. That leads to one inescapable conclusion:

Most of the remaining fossil fuel reserves must stay buried in the ground.

We’ve never done that before. There is no political or economic system anywhere in the world currently that can persuade an energy company to leave a valuable fossil fuel resource untapped. There is no government in the world that has demonstrated the ability to forgo the economic wealth from natural resource extraction, for the good of the planet as a whole. We’re lacking both the political will and the political institutions to achieve this. Finding a way to achieve this presents us with a challenge far bigger than we ever imagined.

You can download all of Climate Change 2013: The Physical Science Basishere. Click below to read any part of this series:

(7) To stay below 2 °C of warming, the world must become carbon negative

Only one of the four future scenarios (RCP2.6) shows us staying below the UN’s commitment to no more than 2 ºC of warming. In RCP2.6, emissions peak soon (within the next decade or so), and then drop fast, under a stronger emissions reduction policy than anyone has ever proposed in international negotiations to date. For example, the post-Kyoto negotiations have looked at targets in the region of 80% reductions in emissions over say a 50 year period. In contrast, the chart below shows something far more ambitious: we need more than 100% emissions reductions. We need to become carbon negative:

(Figure 12.46) a) CO2 emissions for the RCP2.6 scenario (black) and three illustrative modified emission pathways leading to the same warming, b) global temperature change relative to preindustrial for the pathways shown in panel (a).

The graph on the left shows four possible CO2 emissions paths that would all deliver the RCP2.6 scenario, while the graph on the right shows the resulting temperature change for these four. They all give similar results for temperature change, but differ in how we go about reducing emissions. For example, the black curve shows CO2 emissions peaking by 2020 at a level barely above today’s, and then dropping steadily until emissions are below zero by about 2070. Two other curves show what happens if emissions peak higher and later: the eventual reduction has to happen much more steeply. The blue dashed curve offers an implausible scenario, so consider it a thought experiment: if we held emissions constant at today’s level, we have exactly 30 years left before we would have to instantly reduce emissions to zero forever.

Notice where the zero point is on the scale on that left-hand graph. Ignoring the unrealistic blue dashed curve, all of these pathways require the world to go net carbon negative sometime soon after mid-century. None of the emissions targets currently being discussed by any government anywhere in the world are sufficient to achieve this. We should be talking about how to become carbon negative.

One further detail. The graph above shows the temperature response staying well under 2°C for all four curves, although the uncertainty band reaches up to 2°C. But note that this analysis deals only with CO2. The other greenhouse gases have to be accounted for too, and together they push the temperature change right up to the 2°C threshold. There’s no margin for error.

You can download all of Climate Change 2013: The Physical Science Basishere. Click below to read any part of this series:

I’ll talk about the first of these here, and the rest in future parts—click to get to any part you want. But before I start, a little preamble.

The IPCC was set up in 1988 as a UN intergovernmental body to provide an overview of the science. Its job is to assess what the peer-reviewed science says, in order to inform policymaking, but it is not tasked with making specific policy recommendations. The IPCC and its workings seem to be widely misunderstood in the media. The dwindling group of people who are still in denial about climate change particularly like to indulge in IPCC-bashing, which seems like a classic case of ‘blame the messenger’. The IPCC itself has a very small staff (no more than a dozen or so people). However, the assessment reports are written and reviewed by a very large team of scientists (several thousands), all of whom volunteer their time to work on the reports. The scientists are are organised into three working groups: WG1 focuses on the physical science basis, WG2 focuses on impacts and climate adaptation, and WG3 focuses on how climate mitigation can be achieved.

I wrote about the WG1 draft in October, but John has solicited this post for Azimuth only now. By now, the draft I’m talking about here has undergone some minor editing/correcting, and some of the figures might have ended up re-drawn. Even so, most of the text is unlikely to have changed, and the major findings can be considered final.

In this post and the parts to come I’ll give my take on the most important findings, along with a key figure to illustrate each.

(1) The warming is unequivocal

The text of the summary for policymakers says:

Warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprecedented over decades to millennia. The atmosphere and ocean have warmed, the amounts of snow and ice have diminished, sea level has risen, and the concentrations of greenhouse gases have increased.

Unfortunately, there has been much play in the press around a silly idea that the warming has “paused” in the last decade. If you squint at the last few years of the top graph, you might be able to convince yourself that the temperature has been nearly flat for a few years, but only if you cherry pick your starting date, and use a period that’s too short to count as climate. When you look at it in the context of an entire century and longer, such arguments are clearly just wishful thinking.

The other thing to point out here is that the rate of warming is unprecedented:

With very high confidence, the current rates of CO2, CH4 and N2O rise in atmospheric concentrations and the associated radiative forcing are unprecedented with respect to the highest resolution ice core records of the last 22,000 years

and there is

medium confidence that the rate of change of the observed greenhouse gas rise is also unprecedented compared with the lower resolution records of the past 800,000 years.

In other words, there is nothing in any of the ice core records that is comparable to what we have done to the atmosphere over the last century. The earth has warmed and cooled in the past due to natural cycles, but never anywhere near as fast as modern climate change.

You can download all of Climate Change 2013: The Physical Science Basishere. It’s also available chapter by chapter here:

This is my first post to Azimuth. It’s a companion to the one by Alaistair Jamieson-Lane. I’m an assistant professor at the University of Waterloo in Canada with the Centre for Knowledge Integration, or CKI. Through our teaching and research, the CKI focuses on integrating what appears, at first blush, to be drastically different fields in order to make the world a better place. The very topics I would like to cover today, which are mathematics and policy design, are an example of our flavour of knowledge integration. However, before getting into that, perhaps some background on how I got here would be helpful.

The conundrum of complex systems

For about eight years, I have focused on various problems related to long-term forecasting of social and technological change (long-term meaning in excess of 10 years). I became interested in these problems because they are particularly relevant to how we understand and respond to global environmental changes such as climate change.

In case you don’t know much about global warming or what the fuss is about, part of what makes the problem particularly difficult is that the feedback from the physical climate system to human political and economic systems is exceedingly slow. It is so slow, that under traditional economic and political analyses, an optimal policy strategy may appear to be to wait before making any major decisions – that is, wait for scientific knowledge and technologies to improve, or at least wait until the next election [1]. Let somebody else make the tough (and potentially politically unpopular) decisions!

The problem with waiting is that the greenhouse gases that scientists are most concerned about stay in the atmosphere for decades or centuries. They are also churned out by the gigatonne each year. Thus the warming trends that we have experienced for the past 30 years, for instance, are the cumulative result of emissions that happened not only recently but also long ago—in the case of carbon dioxide, as far back as the turn of the 20th century. The world in the 1910s was quainter than it is now, and as more economies around the globe industrialize and modernize, it is natural to wonder: how will we manage to power it all? Will we still rely so heavily on fossil fuels, which are the primary source of our carbon dioxide emissions?

Such questions are part of what makes climate change a controversial topic. Present-day policy decisions about energy use will influence the climatic conditions of the future, so what kind of future (both near-term and long-term) do we want?

Futures studies and trying to learn from the past

Many approaches can be taken to answer the question of what kind of future we want. An approach familiar to the political world is for a leader to espouse his or her particular hopes and concerns for the future, then work to convince others that those ideas are more relevant than someone else’s. Alternatively, economists do better by developing and investigating different simulations of economic developments over time; however, the predictive power of even these tools drops off precipitously beyond the 10-year time horizon.

The limitations of these approaches should not be too surprising, since any stockbroker will say that when making financial investments, past performance is not necessarily indicative of future results. We can expect the same problem with rhetorical appeals, or economic models, that are based on past performances or empirical (which also implies historical) relationships.

A different take on foresight

A different approach avoids the frustration of proving history to be a fickle tutor for the future. By setting aside the supposition that we must be able to explain why the future might play out a particular way (that is, to know the ‘history’ of a possible future outcome), alternative futures 20, 50, or 100 years hence can be conceptualized as different sets of conditions that may substantially diverge from what we see today and have seen before. This perspective is employed in cross-impact balance analysis, an algorithm that searches for conditions that can be demonstrated to be self-consistent [3].

Findings from cross-impact balance analyses have been informative for scientific assessments produced by the Intergovernmental Panel on Climate Change Research, or IPCC. To present a coherent picture of the climate change problem, the IPCC has coordinated scenario studies across economic and policy analysts as well as climate scientists since the 1990s. Prior to the development of the cross-impact balance method, these researchers had to do their best to identify appropriate ranges for rates of population growth, economic growth, energy efficiency improvements, etc. through their best judgment.

A retrospective using cross-impact balances on the first Special Report on Emissions Scenarios found that the researchers did a good job in many respects. However, they underrepresented the large number of alternative futures that would result in high greenhouse gas emissions in the absence of climate policy [4].

As part of the latest update to these coordinated scenarios, climate change researchers decided it would be useful to organize alternative futures according socio-economic conditions that pose greater or fewer challenges to mitigation and adaptation. Mitigation refers to policy actions that decrease greenhouse gas emissions, while adaptation refers to reducing harms due to climate change or to taking advantage of benefits. Some climate change researchers argued that it would be sufficient to consider alternative futures where challenges to mitigation and adaptation co-varied, e.g. three families of futures where mitigation and adaptation challenges would be low, medium, or high.

Instead, cross-impact balances revealed that mixed-outcome futures—such as socio-economic conditions simultaneously producing fewer challenges to mitigation but greater challenges to adaptation—could not be completely ignored. This counter-intuitive finding, among others, brought the importance of quality of governance to the fore [5].

Although it is generally recognized that quality of governance—e.g. control of corruption and the rule of law—affects quality of life [6], many in the climate change research community have focused on technological improvements, such as drought-resistant crops, or economic incentives, such as carbon prices, for mitigation and adaptation. The cross-impact balance results underscored that should global patterns of quality of governance across nations take a turn for the worse, poor governance could stymie these efforts. This is because the influence of quality of governance is pervasive; where corruption is permitted at the highest levels of power, it may be permitted at other levels as well—including levels that are responsible for building schools, teaching literacy, maintaining roads, enforcing public order, and so forth.

The cross-impact balance study revealed this in the abstract, as summarized in the example matrices below. Alastair included a matrix like these in his post, where he explained that numerical judgments in such a matrix can be used to calculate the net impact of simultaneous influences on system factors. My purpose in presenting these matrices is a bit different, as the matrix structure can also explain why particular outcomes behave as system attractors.

In this example, a solid light gray square means that the row factor directly influences the column factor some amount, while white space means that there is no direct influence:

Dark gray squares along the diagonal have no meaning, since everything is perfectly correlated to itself. The pink squares highlight the rows for the factors “quality of governance” and “economy.” The importance of these rows is more apparent here; the matrix above is a truncated version of this more detailed one:

(Click to enlarge.)

The pink rows are highlighted because of a striking property of these factors. They are the two most influential factors of the system, as you can see from how many solid squares appear in their rows. The direct influence of quality of governance is second only to the economy. (Careful observers will note that the economy directly influences quality of governance, while quality of governance directly influences the economy). Other scholars have meticulously documented similar findings through observations [7].

As a method for climate policy analysis, cross-impact balances fill an important gap between genius forecasting (i.e., ideas about the far-off future espoused by one person) and scientific judgments that, in the face of deep uncertainty, are overconfident (i.e. neglecting the ‘fat’ or ‘long’ tails of a distribution).

Wanted: intrepid explorers of future possibilities

However, alternative visions of the future are only part of the information that’s needed to create the future that is desired. Descriptions of courses of action that are likely to get us there are also helpful. In this regard, the post by Jamieson-Lane describes early work on modifying cross-impact balances for studying transition scenarios rather than searching primarily for system attractors.

This is where you, as the mathematician or physicist, come in! I have been working with cross-impact balances as a policy analyst, and I can see the potential of this method to revolutionize policy discussions—not only for climate change but also for policy design in general. However, as pointed out by entrepreneurship professor Karl T. Ulrich, design problems are NP-complete. Those of us with lesser math skills can be easily intimidated by the scope of such search problems. For this reason, many analysts have resigned themselves to ad hoc explorations of the vast space of future possibilities. However, some analysts like me think it is important to develop methods that do better. I hope that some of you Azimuth readers may be up for collaborating with like-minded individuals on the challenge!

References

The graph of carbon emissions is from reference [2]; the pictures of the matrices are adapted from reference [5]:

How To Write Math Here:

You need the word 'latex' right after the first dollar sign, and it needs a space after it. Double dollar signs don't work, and other limitations apply, some described here. You can't preview comments here, but I'm happy to fix errors.